Latest Trend and Challenges in Machine Learning– and Deep Learning–Based Computational Techniques in Poultry Health and Disease Management: A Review by Shwetha V., Maddodi B. S., Vijaya Laxmi, Abhinav Kumar, Sakshi Shrivastava

“…The advancement of machine learning (ML)– and deep learning (DL)–based algorithms are boons for poultry health and disease management. …”
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Functional control of the technical condition method for aircraft control system sensors under complete parametric uncertainty by J. V. Bondarenko, E. Yu. Zybin

“…Fast tuning, fast response and selective sensitivity of the developed algorithms are noted.…”
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Measuring the Dimension Accuracy of Products Created by 3D Printing Technology with the Designed Measuring System by Martin Pollák, Dominik Sabol, Karol Goryl

“…Comprehensive analysis of measurements in combination with advanced algorithms can provide more accurate dimensional characteristics and the prediction of defects. …”
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Knowledge graph convolutional networks with user preferences for course recommendation by Zhong Hua, Jianbai Yang, Weidong Ji

“…Research on KG-enhanced recommendation algorithms has found that the utilization of side information in KGs is crucial for improving accuracy. …”
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Impact of Advanced Agriculture Technologies and Energy Consumption on Crop Yields in Modern Agriculture Using Deep Learning Techniques by Khan Baz, Zhu Zhen, Hashmat Ali

“…First, advanced machine learning algorithms are employed to investigate the combined impact of the farming Product Complexity Index on agricultural yields. …”
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Integrated multiomics analysis identifies potential biomarkers and therapeutic targets for autophagy associated AKI to CKD transition by Yaojun Wang, Qiang Li

“…Single-cell analysis showed that ATP6V1C1 and COPA were specifically expressed in AKI and CKD, which may be related to renal fibrosis. In addition, drug prediction and molecular docking analysis proposed SZ(+)-(S)-202-791 and PDE4 inhibitor 16 as potential therapeutic agents. …”
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Hybrid LSTM–Attention and CNN Model for Enhanced Speech Emotion Recognition by Fazliddin Makhmudov, Alpamis Kutlimuratov, Young-Im Cho

“…Even though deep learning algorithms are actively used in this field, the study of sequence modeling that accounts for the shifts in emotions over time has not been thoroughly explored. …”
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Sentiment Analysis of User Reviews of the AdaKami Online Loan App from the App Store Using SVM and Naive Bayes by Wava Lativa Azzahra, Jamaludin Indra, Rahmat Rahmat, Sutan Faisal

“…The classification model was built using two machine learning algorithms, namely Support Vector Machine (SVM) and Naïve Bayes (NB). …”
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Application of artificial intelligence in the diagnosis and treatment of lacrimal disorders: challenges and opportunities by PENG Xintong, LI Guangyu

“…However, several challenges persist, such as the complexity of multimodal data integration, limitations in model generalization capabilities, and the need for real-time prediction and dynamic adjustments, all of which necessitate continuous technological innovations, algorithm optimization, and interdisciplinary collaborations. …”
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H-DSAE: a hybrid technique to recognize heart disease by K. Uma Maheswari, A. Valarmathi

“…The next phase of the project will focus on developing more advanced classification and features algorithms. This will help improve the efficiency of the system.…”
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Generation of realistic input parameters for simulating atmospheric point-spread functions at astronomical observatories by Claire-Alice Hébert, Joshua E. Meyers, My H. Do, Patricia R. Burchat, LSST Dark Energy Science Collaboration

“…We make quantitative predictions for two-point correlation functions (2PCF) that are used in analyses of cosmic shear. …”
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Comprehensive prevention and control strategy for top coal fire based on the intelligent mine comprehensive management and control platform by Miao ZHAO

“…The existing fire perception and prevention technology and equipment are evaluated, and their problems are pointed out, such as incomplete perception coverage and immature early warning model algorithms. Based on these issues, a comprehensive fire prevention and control center is constructed, and a comprehensive prevention and control strategy is proposed, including fire prediction and early warning, coal spontaneous combustion prevention and treatment strategies, as well as associated disaster prevention and control, and emergency response and rescue strategy previews. …”
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A deep hybrid learning pipeline for accurate diagnosis of ovarian cancer based on nuclear morphology. by Duhita Sengupta, Sk Nishan Ali, Aditya Bhattacharya, Joy Mustafi, Asima Mukhopadhyay, Kaushik Sengupta

“…This novel Deep Hybrid Learning model, though derived from classical machine learning algorithms and standard CNN, showed a training and validation AUC score of 0.99 whereas the test AUC score turned out to be 1.00. …”
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Research on Iterative Learning Semi-active Control for Curve Passing of High-speed Train by Yongjun AI, Chunjun CHEN, Xin LI, Jianrong ZHOU

“…According to the repeatability of train running and the big data, the PD iterative learning control algorithm was designed, and the semi-active control simulation which combined control algorithm with dynamic software was carried out to compare with the results of the passive working conditions. …”
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Adaptive pilot design for OFDM based on deep reinforcement learning by Qiaoshou LIU, Xiong ZHOU, Shuang LIU, Yifeng DENG

“…For orthogonal frequency division multiplexing (OFDM) systems, an adaptive pilot design algorithm based on deep reinforcement learning was proposed.The pilot design problem was formulated as a Markov decision process, where the index of pilot positions was defined as actions.A reward function based on mean squared error (MSE) reduction strategy was formulated, and deep reinforcement learning was employed to update the pilot positions.The pilot was adaptively and dynamically allocated based on channel conditions, thereby utilizing channel characteristics to combat channel fading.The simulation results show that the proposed algorithm has significantly improved channel estimation performance compared with the traditional pilot uniform allocation scheme under three typical multipath channels of 3GPP.…”
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Coordinated beamforming for cognitive multi-cell networks with wiretap channels by Dong-hua CHEN, Xiu-xiu ZHANG, Wei-bo XIE

“…Owing to the coupling among the vectors to be optimized，the problem becomes non-convex and non-linear.Accordingly，a centralized coordinated beamforming design method was proposed by constraining the leakage interference and using the semi-definite relaxation，and on the base of it，a decentralized algorithm was also proposed by decomposing the centralized design problem into a group of sub-problems on each cell’s base by using dual decomposition.Simulation results show that the proposed schemes make effective reduction in power consumption while guarantee the legal users’ secrecy rate requirement and the cognitive interference constraint.Moreover，the proposed decentralized method not only reduces the computational complexity，but also has the same performance as the centralized algorithm.…”
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In vivo efficacy of the boron-pleuromutilin AN11251 against Wolbachia of the rodent filarial nematode Litomosoides sigmodontis. by Alexandra Ehrens, Christopher S Lunde, Robert T Jacobs, Dominique Struever, Marianne Koschel, Stefan J Frohberger, Franziska Lenz, Martina Fendler, Joseph D Turner, Stephen A Ward, Mark J Taylor, Yvonne R Freund, Rianna Stefanakis, Eric Easom, Xianfeng Li, Jacob J Plattner, Achim Hoerauf, Marc P Hübner

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The Value of MRI and Radiomics for the Diagnostic Evaluation of Thyroid-Associated Ophthalmopathy by Weiyi Zhou, Yan Song, Jufeng Shi, Tuo Li

“…The early diagnosis and prediction of these refractory and relapsed patients is essential. …”
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Using rule-based machine learning for candidate disease gene prioritization and sample classification of cancer gene expression data. by Enrico Glaab, Jaume Bacardit, Jonathan M Garibaldi, Natalio Krasnogor

“…Increasing the interpretability of prediction models while retaining a high accuracy would help to exploit the information content in microarray data more effectively. …”
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Detection of the Pin Defects of Power Transmission Lines Based on Improved TPH-MobileNetv3 by Mengxuan Li, Jingshan Han, Zhi Yang, Bin Zhao, Peng Liu

“…Moreover, compared with the mainstream algorithms with the same detection accuracy, this algorithm not only reduces the model size and significantly enhances detection efficiency but also satisfies the requirement of edge image processing of power inspection.…”
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